So far in this chapter, we have focused on data collection for empirical research (systematic observation of primary or secondary sources). However, many undergraduate theses take the shape of systematic literature review (meta analysis), argumentative essays or theoretical arguments. In this section, we comment on data collection for these.

Systematic Literature Review

Systematic reviews (or meta-analyses) “attempt to collate all empirical evidence that fits pre-specified eligibility criteria to answer a specific research question. It uses explicit, systematic methods that are selected with a view to minimizing bias, thus providing reliable findings from which conclusions can be drawn and decisions made” (Liberati et al, 2009, p. E3; Oxman & Guyatt, 1993). According to Liberati et al (2009, p. e3), systematic reviews are characterized by the following:

• a clearly stated set of objectives with an explicit, reproducible methodology;
• a systematic search that attempts to identify all studies that would meet the eligibility criteria
• an assessment of the validity of the findings of the included studies, for example through the assessment of risk of bias
• systematic presentation, and synthesis, of the characteristics and findings of the included studies.

While we will not review the process of conducting systematic literature review (see Liberati et al, 2009 for full details including checklists for procedures; see also Oxman & Guyatt, 1993), we highlight some key consideration for data collection in this section. We also encourage you to consult Chapter 6 (literature review) as well as UBC library’s “Planning your Review”, which will provide you information about systematic literature reviews and more. As with other procedures, for systematic literature review, the ‘right’ amount of literature collected will depend on your research question and the amount of research covered in your area. Since your research is devoted to a literature review, however, you should endeavour to cover all the relevant literature with regard to your research question or intended contribution.

There are two primary steps in the data collection process for systematic reviews. The first is establishing a research protocol or plan of how the search will be conducted. The UoM (2022) provides the following five guidelines for developing research protocols: (1) decide on the objectives of the review; (2) determine how the systematic review will be conducted (methods and processes). This will be similar to the suggestions for conducting textual data above; (3) establish eligibility criteria for the studies that will be included; (4) determine how you will extract data from the studies (see Alexander’s testimonial for how he used NViVo; simple copy and paste works as well); (5) determine what analyses will be performed (e.g., thematic, discourse, content analysis etc).

The second step is conducting the literature search. Again we encourage you to review Chapter 6 (Literature Review) for guidance in conducting a literature search. However, it is important to keep records of the databases included in the year, the years covered, dates when the searches were conducted, search terms and strategies and the number of results obtained (UoM, 2022). These details will inform your methodology (see Chapter 7).

Argumentative Essays and Theoretical Theses

As theoretical dissertations aim to propose either new conceptual models or establish the effects of the existing ones when applying the theory to societal issues (Cropanzano, 2009), you will need to start with a particular theory in mind. You will then examine how the application of such theory would help us to better understand or solve a problem or fill a gap in the scholarship (Cropanzano, 2009). Hence, the data collection process for argumentative essays and theoretical theses are similar to that for conducting systematic review –it is literature driven. However, researchers might choose to employ theoretical sampling to guide the data collection process. Theoretical sampling, according to Corbin & Strauss (2008, p. 143) is “ a method of data collection based on concepts/themes derived from data. The purpose of theoretical sampling is to collect data from places, people, and events that will maximize opportunities to develop concepts in terms of their properties and dimensions, uncover variations, and identify relationships between concepts.” Theoretical sampling is an intense process, wherein the researcher tries to reach saturation –the point at which no new data is found (Corbin & Strauss, 2008). It involves three processes: (1) selecting cases that conforms to the researchers’ central argument/ theory; (2) selecting cases that deviates from the central argument/theory; and (3) adapting the sample sizes of cases that either conform or deviates in order to explore emerging ideas or generalizations. As with all methodological choices, the researcher needs to determine and justify what cases are included and why, and establish a criteria for how cases are selected (Silverman & Marvasti, 2008). Because theoretical papers try to establish new hypotheses and theories, the method of data collection is inductive, iterative and often seen as a component of grounded theory (Corbin & Strauss, 2008).

References

Corbin, J. & Strauss, A. (2008). Basics of qualitative research (3rd edition). Sage publications.

Cropanzano, R. (2009). Writing Non-Empirical Article for Journal of Management: General Thoughts and Suggestions. Journal of Management, 35(6), 1304-1311.

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P., … & Moher (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of clinical epidemiology, 62(10), e1-e34.

Oxman, A. D., & Guyatt, G. H. (1993). The science of reviewing research. Annals of the New York Academy of Sciences, 703(1), 125-134.

Silverman, D. &Marvasti, A. (2008). Doing Qualitative Research- A comprehensive Guide. Sage Publications

UoM, 2022